Radar imaging by a tomographic target density function

2015 ◽  
Author(s):  
A. Demirkol ◽  
R.F. Cinar ◽  
Z. Demir
Keyword(s):  
Density Function ◽  
Radar Imaging ◽  
Target Density

scholarly journals Kalman filter aided target density function for radar imaging

2019 ◽  
Vol 2019 (19) ◽  
pp. 5602-5604 ◽  
Author(s):  
Ridvan Firat Cinar ◽  
Fatih Kocadag ◽  
Askin Demirkol
Keyword(s):  
Kalman Filter ◽  
Density Function ◽  
Radar Imaging ◽  
Target Density

The structure of amorphous and polycrystalline materials using energy-filtered RDF analysis

1992 ◽  
Vol 50 (2) ◽  
pp. 1190-1191
Author(s):  
David Cockayne ◽  
David McKenzie
Keyword(s):  
Electron Diffraction ◽  
Diffraction Pattern ◽  
Density Function ◽  
Electron Diffraction Pattern ◽  
Polycrystalline Materials ◽  
Nearest Neighbour ◽  
X Ray ◽  
Selected Area Electron Diffraction ◽  
Reduced Density ◽  
System F

The technique of Electron Reduced Density Function (RDF) analysis has ben developed into a rapid analytical tool for the analysis of small volumes of amorphous or polycrystalline materials. The energy filtered electron diffraction pattern is collected to high scattering angles (currendy to s = 2 sinθ/λ = 6.5 Å-1) by scanning the selected area electron diffraction pattern across the entrance aperture to a GATAN parallel energy loss spectrometer. The diffraction pattern is then converted to a reduced density function, G(r), using mathematical procedures equivalent to those used in X-ray and neutron diffraction studies.Nearest neighbour distances accurate to 0.01 Å are obtained routinely, and bond distortions of molecules can be determined from the ratio of first to second nearest neighbour distances. The accuracy of coordination number determinations from polycrystalline monatomic materials (eg Pt) is high (5%). In amorphous systems (eg carbon, silicon) it is reasonable (10%), but in multi-element systems there are a number of problems to be overcome; to reduce the diffraction pattern to G(r), the approximation must be made that for all elements i,j in the system, fj(s) = Kji fi,(s) where Kji is independent of s.

Analytical Representation of the Density Function of Normal Distribution of Noise

2015 ◽  
Vol 47 (8) ◽  
pp. 24-40 ◽  
Author(s):  
Telman Abbas ogly Aliev ◽  
Naila F. Musaeva ◽  
Matanat Tair kyzy Suleymanova ◽  
Bahruz Ismail ogly Gazizade
Keyword(s):  
Normal Distribution ◽  
Density Function ◽  
Analytical Representation

Technology for Calculating the Parameters of the Density Function of the Normal Distribution of the Useful Component in a Noisy Process

2016 ◽  
Vol 48 (4) ◽  
pp. 39-55 ◽  
Author(s):  
Telman Abbas ogly Aliev ◽  
Naila Fuad kyzy Musaeva ◽  
Matanat Tair kyzy Suleymanova ◽  
Bahruz Ismail ogly Gazizade
Keyword(s):  
Normal Distribution ◽  
Density Function
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